Introduction to CUDA Kernel Programming | CodeSignal Learn

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intermediate

Introduction to CUDA Kernel Programming

Embedded Systems & Firmware

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4 courses

75 practices

9 hours

Learn CUDA from the ground up by managing GPU memory, launching 1D and 2D kernels, optimizing with shared memory, and building practical image-processing pipelines for graphics-oriented parallel computing.

4.69

254 learners

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Verified skills you'll gain

INTERMEDIATE

GPU Architecture and Memory Hierarchy

INTERMEDIATE

GPU Programming Models and Frameworks

Tools you'll use

CUDA

Course 1

CUDA Basics and 1D Operations

4 lessons

22 practices

In this course, you will dive into the core mechanics of heterogeneous computing using C++ and CUDA. You will learn how to allocate GPU memory safely, transfer datasets correctly between the CPU and GPU, and configure block dimensions to execute and verify your first one-dimensional kernels.

Course 2

2D Grids and Matrix Math

3 lessons

15 practices

Master 2D thread indexing in CUDA by mapping multidimensional grids to linear memory. You will implement row-major indexing, build a naive matrix multiplication kernel, and apply 2D grid-stride loops. These skills allow you to process large, rectangular datasets efficiently while ensuring your kernels remain scalable and flexible across various GPU architectures.

Course 3

Shared Memory Optimization

4 lessons

22 practices

In this course, you will tackle global memory latency by harnessing the power of fast, on-chip shared memory. You will learn to synchronize threads using shared memory, implement a boundary-safe tiled matrix multiplication algorithm, and empirically compare it against a naive implementation using validated benchmarks.

Course 4

Image Processing with CUDA

3 lessons

16 practices

Apply your CUDA skills to image buffers by processing pixels on the GPU. You will map RGB data to threads, handle boundary conditions, and build a pipeline chaining grayscale conversion and Sobel edge detection. Finally, you will validate and export results, mastering real-world GPU image manipulation.

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